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searching for Sample complexity 20 found (28 total)

Occam learning (1,710 words) [view diff] exact match in snippet view article find links to article

the Occam framework can be used to produce tighter bounds on the sample complexity of classical problems including conjunctions, conjunctions with few

Bretagnolle–Huber inequality (1,629 words) [view diff] no match in snippet view article find links to article

In information theory, the Bretagnolle–Huber inequality bounds the total variation distance between two probability distributions P {\displaystyle P} and

Distribution learning theory (3,845 words) [view diff] exact match in snippet view article find links to article

distributions C {\displaystyle \textstyle C} . This quantity is called sample complexity of the learning algorithm. In order for the problem of distribution

Vapnik–Chervonenkis dimension (2,798 words) [view diff] no match in snippet view article find links to article

training-error. This is due to overfitting). The VC dimension also appears in sample-complexity bounds. A space of binary functions with VC dimension D {\displaystyle

Shai Ben-David (559 words) [view diff] exact match in snippet view article find links to article

2014). He received the best paper award at NeurIPS 2018. for work on sample complexity of distribution learning problems. He was the President of the Association

Scenario optimization (1,258 words) [view diff] exact match in snippet view article find links to article

approach, named "Repetitive Scenario Design" aims at reducing the sample complexity of the solution by repeatedly alternating a scenario design phase

Thomas G. Dietterich (2,778 words) [view diff] case mismatch in snippet view article find links to article

Siddiqui, Alan Fern, Thomas G. Dietterich, Shubhomoy Das (2016). Finite Sample Complexity of Rare Pattern Anomaly Detection. Uncertainty in Artificial Intelligence

Thompson sampling (1,657 words) [view diff] case mismatch in snippet view article find links to article

Daniel J. Russo and Benjamin Van Roy (2013), "Eluder Dimension and the Sample Complexity of Optimistic Exploration", Advances in Neural Information Processing

Quantum machine learning (10,788 words) [view diff] exact match in snippet view article find links to article

of examples needed: for every concept class, classical and quantum sample complexity are the same up to constant factors. However, for learning under some

Vlad Voroninski (621 words) [view diff] exact match in snippet view article find links to article

connected the fields of deep learning and inverse problems, resolving the sample complexity bottleneck for compressive phase retrieval. Voroninski was awarded

Chemical biology (6,098 words) [view diff] exact match in snippet view article find links to article

barrier for their detection. Chemical biology methods can reduce sample complexity by selective enrichment using affinity chromatography. This involves

Ensemble learning (6,685 words) [view diff] exact match in snippet view article find links to article

David; Kearns, Michael; Schapire, Robert E. (1994). "Bounds on the sample complexity of Bayesian learning using information theory and the VC dimension"

Large width limits of neural networks (869 words) [view diff] exact match in snippet view article find links to article

Cite journal requires |journal= (help) Bartlett, P.L. (1998). "The sample complexity of pattern classification with neural networks: the size of the weights

Grigory Yaroslavtsev (923 words) [view diff] case mismatch in snippet view article find links to article

Artificial Intelligence). Retrieved 8 August 2023. "Tree Learning: Optimal Sample Complexity and Algorithms" (PDF). AAAI 2023 (37th AAAI Conference on Artificial

Proteomics (9,070 words) [view diff] exact match in snippet view article find links to article

below). For the analysis of complex biological samples, a reduction of sample complexity is required. This may be performed off-line by one-dimensional or

Sparse Fourier transform (1,624 words) [view diff] exact match in snippet view article find links to article

"Sparse fourier transform in any constant dimension with nearly-optimal sample complexity in sublinear time". Proceedings of the forty-eighth annual ACM symposium

Matrix completion (6,062 words) [view diff] exact match in snippet view article find links to article

1 / ϵ ) ) {\displaystyle O(\log(1/\epsilon ))} steps. In terms of sample complexity ( | Ω | {\displaystyle |\Omega |} ), theoretically, Alternating Minimization

Loss functions for classification (4,212 words) [view diff] exact match in snippet view article find links to article

excessively, leading to slower convergence rates (with regards to sample complexity) than for the logistic loss or hinge loss functions. In addition,

Boson sampling (7,102 words) [view diff] exact match in snippet view article find links to article

; Aolita, L.; Eisert, J. (2013). "Boson-Sampling in the light of sample complexity". arXiv:1306.3995 [quant-ph]. Aaronson, Scott; Arkhipov, Alex (2013)

Reinforcement learning from human feedback (8,617 words) [view diff] exact match in snippet view article find links to article

its policy immediately, have been mathematically studied proving sample complexity bounds for RLHF under different feedback models. In the offline data